main.py

from fastapi import FastAPI, Request
from pydantic import BaseModel
from fastapi.middleware.cors import CORSMiddleware
from g4f.client import Client
from fastapi.responses import StreamingResponse

# Initialize the AI client
client = Client()

# FastAPI app
app = FastAPI()

# CORS Middleware (so JS from browser can access it too)
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Change "*" to your frontend URL for better security
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Request body model
class Question(BaseModel):
    question: str

async def generate_response_chunks(prompt: str):
    try:
        response = client.chat.completions.create(
            model="gpt-4",  # Use a supported model
            messages=[
                {"role": "user", "content": prompt},
                {"role": "system", "content": "You are a helpful AI assistant created by abdullah ali who is very intelegent and he is 13 years old and live in lahore."}
            ],
            stream=True  # Enable streaming
        )

        for part in response:
            content = part.choices[0].delta.content
            if content:
                yield content
                
    except Exception as e:
        yield f"Error occurred: {e}"

@app.post("/ask")
async def ask(question: Question):
    return StreamingResponse(
        generate_response_chunks(question.question),
        media_type="text/plain"
    )